Prospective comparison of the HEP score and 4Ts score for the diagnosis of heparin-induced thrombocytopenia
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Bibliographic record
Abstract
Abstract The HIT Expert Probability (HEP) score compared favorably with the 4Ts score in a retrospective study. We assessed the diagnostic accuracy of the HEP score compared with the 4Ts score in a prospective cohort of 310 patients with suspected heparin-induced thrombocytopenia (HIT). A member of the clinical team calculated the HEP score and 4Ts score. An independent panel adjudicated HIT status based on a clinical summary as well as the results of HIT laboratory testing. The prevalence of HIT in the study population was 14.7%. At a cutoff of ≥3, the HEP score was 95.3% sensitive (95% confidence interval [CI], 84.2-99.4) and 35.7% specific (95% CI, 29.8-42.0) for HIT. A 4Ts score of ≥4 had a sensitivity of 97.7% (95% CI, 86.2-99.8) and specificity of 32.9% (95% CI, 27.2-39.1). The areas under the receiver operating characteristic (ROC) curves (AUCs) for the HEP score and 4Ts score were similar (0.81 [95% CI, 0.74-0.87] vs 0.76 [95% CI, 0.69-0.83]; P = .12). The HEP score exhibited a significantly higher AUC than the 4Ts score in patients in the intensive care unit (ICU) (0.86 vs 0.79; P = .03). Among trainee scorers, the HEP score performed significantly better than the 4Ts score (AUC, 0.80 vs 0.73; P = .03). Our data suggest that either the 4Ts score or the HEP score may be used in clinical practice. The HEP score may be preferable in ICU patients and among less experienced clinicians.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it